Peer - Mediated Distributed Knowledge Management

Distributed Knowledge Management is an approach to knowledge management based on the principle that the multiplicity (and heterogeneity) of perspectives within complex organizations is not be viewed as an obstacle to knowledge exploitation, but rather as an opportunity that can foster innovation and creativity. Despite a wide agreement on this principle, most current KM systems are based on the idea that all perspectival aspects of knowledge should be eliminated in favor of an objective and general representation of knowledge. In this paper we propose a peer-to-peer architecture (called KEx), which embodies the principle above in a quite straightforward way: (i) each peer (called a K-peer) provides all the services needed to create and organize "local" knowledge from an individual's or a group's perspective, and (ii) social structures and protocols of meaning negotiation are introduced to achieve semantic coordination among autonomous peers (e.g., when searching documents from other K-peers). A first version of the system, called KEx, is imple-mented as a knowledge exchange level on top of JXTA

Cooperative Approach for Composite Ontology Mapping

This paper proposes a cooperative approach for composite ontology mapping. We first present an extended classification of automated ontology matching and propose an automatic composite solution for the matching problem based on cooperation. In our proposal, agents apply individual mapping algorithms and cooperate in order to change their individual results. We assume that the approaches are complementary to each other and their combination produces better results than the individual ones. Next, we compare our model with three state of the art matching systems. The results are promising specially for what concerns precision and recall. Finally, we propose an argumentation formalism as an extension of our initial model. We compare our argumentation model with the matching systems, showing improvements on the results

"Implicature-Laden" Elicitations in Talk Radio Shows

Indirect elicitations in talk radio programmes on BBC Radio are not uncommon, notwithstanding, misunderstanding between the host and his conversational partner is not frequent. Investigating some of the reasons this paper focuses on how the socio-cultural and cognitive factors of the context interweave in discourse. The author suggests that valid interpretation and appropriate response to inferred elicitations can be best explained within the framework of Relevance Theory, and more specifically, with the presumption of accessibility of schemas obtained from the cognitive environment of the discourse partners. Through examples of empirical research the paper aims to reveal how the mutual knowledge of the participants controls discourse via the mental processes occurring in the interaction of two minds

A tool for the automatic and manual annotation of biomedical documents

The techniques developed within the field of Biomedical Text Mining (BioTM) have been mainly tested and evaluated over a set of known corpora built by a few researchers with a specific goal or to support scientific competitions. The generalized use of BioTM software therefore requires that an enlarged set of corpora is made available covering a wider range of biomedical research topics. This work proposes a software tool that facilitates the task of building a BioTM corpus by providing a userfriendly and interoperable tool that allows both automatic and manual annotation of biomedical documents (supporting both abstracts and full text). This tool is also integrated in a more comprehensive BioTM framework.Fundação para a Ciência e a Tecnologia (FCT

An Ontology-Based Assistant For Analyzing Agents\u27 Activities

This thesis reports on work in progress on software that helps an analyst identify and analyze activities of actors (such as vehicles) in an intelligence-relevant scenario. A system is being developed to aid intelligence analysts, IAGOA ((Intelligence Analyst’s Geospatial and Ontological Assistant). Analysis may be accomplished by retrieving simulated satellite data of ground vehicles and interacting with software modules that allow the analyst to conjecture the activities in which the actor is engaged along with the (largely geospatial and temporal) features of the area of operation relevant to the natures of those activities. Activities are conceptualized by ontologies. The research relies on natural language components (semantic frames) gathered from the FrameNet lexical database, which captures the semantics of lexical items with an ontology using OWL. The software has two components, one for the analyst, and one for a modeler who produces HTML and parameterized KML documents used by the analyst. The most significant input to the modeler software is the FrameNet OWL file, and the interface for the analyst and, to some extent, the modeler is provided by the Google Earth API

Dealing with uncertain entities in ontology alignment using rough sets

This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Ontology alignment facilitates exchange of knowledge among heterogeneous data sources. Many approaches to ontology alignment use multiple similarity measures to map entities between ontologies. However, it remains a key challenge in dealing with uncertain entities for which the employed ontology alignment measures produce conflicting results on similarity of the mapped entities. This paper presents OARS, a rough-set based approach to ontology alignment which achieves a high degree of accuracy in situations where uncertainty arises because of the conflicting results generated by different similarity measures. OARS employs a combinational approach and considers both lexical and structural similarity measures. OARS is extensively evaluated with the benchmark ontologies of the ontology alignment evaluation initiative (OAEI) 2010, and performs best in the aspect of recall in comparison with a number of alignment systems while generating a comparable performance in precision

A Cooperative Approach for Composite Ontology Matching

Ontologies have proven to be an essential element in a range of applications in which knowl-edge plays a key role. Resolving the semantic heterogeneity problem is crucial to allow the interoperability between ontology-based systems. This makes automatic ontology matching, as an anticipated solution to semantic heterogeneity, an important, research issue. Many dif-ferent approaches to the matching problem have emerged from the literature. An important issue of ontology matching is to find effective ways of choosing among many techniques and their variations, and then combining their results. An innovative and promising option is to formalize the combination of matching techniques using agent-based approaches, such as cooperative negotiation and argumentation. In this thesis, the formalization of the on-tology matching problem following an agent-based approach is proposed. Such proposal is evaluated using state-of-the-art data sets. The results show that the consensus obtained by negotiation and argumentation represent intermediary values which are closer to the best matcher. As the best matcher may vary depending on specific differences of multiple data sets, cooperative approaches are an advantage. *** RESUMO - Ontologias são elementos essenciais em sistemas baseados em conhecimento. Resolver o problema de heterogeneidade semântica é fundamental para permitira interoperabilidade entre sistemas baseados em ontologias. Mapeamento automático de ontologias pode ser visto como uma solução para esse problema. Diferentes e complementares abordagens para o problema são propostas na literatura. Um aspecto importante em mapeamento consiste em selecionar o conjunto adequado de abordagens e suas variações, e então combinar seus resultados. Uma opção promissora envolve formalizara combinação de técnicas de ma-peamento usando abordagens baseadas em agentes cooperativos, tais como negociação e argumentação. Nesta tese, a formalização do problema de combinação de técnicas de ma-peamento usando tais abordagens é proposta e avaliada. A avaliação, que envolve conjuntos de testes sugeridos pela comunidade científica, permite concluir que o consenso obtido pela negociação e pela argumentação não é exatamente a melhoria de todos os resultados individuais, mas representa os valores intermediários que são próximo da melhor técnica. Considerando que a melhor técnica pode variar dependendo de diferencas específicas de múltiplas bases de dados, abordagens cooperativas são uma vantagem